Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.

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Title: Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.
Authors: Lee EY; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Dinh BL; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA., Tang J; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Streicher SA; Population Sciences in the Pacific Program, Cancer Center, University of Hawai'i, Honolulu, HI, USA., Wang X; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Biswas S; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Tian H; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Yu X; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Taparra K; Department of Radiation Oncology at the David Geffen School of Medicine, University of California, Los Angeles, CA, USA.; Department of Health Policy and Management at the School of Public Health, University of California, Los Angeles, CA, USA., Naseri T; Ministry of Health, Apia, Samoa.; Department of Epidemiology, Brown University, Providence, RI, USA., Viali S; Oceania University of Medicine, Apia, Samoa.; Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA., Weeks DE; Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.; Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA., Carlson JC; Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.; Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA., Haiman CA; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA., Marchand LL; Population Sciences in the Pacific Program, Cancer Center, University of Hawai'i, Honolulu, HI, USA., Maskarinec G; Population Sciences in the Pacific Program, Cancer Center, University of Hawai'i, Honolulu, HI, USA., Wilkens LR; Population Sciences in the Pacific Program, Cancer Center, University of Hawai'i, Honolulu, HI, USA., Park SY; Population Sciences in the Pacific Program, Cancer Center, University of Hawai'i, Honolulu, HI, USA., Chiang CWK; Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA. charleston.chiang@med.usc.edu.; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. charleston.chiang@med.usc.edu.; Norris Comprehensive Cancer Center, Los Angeles, CA, USA. charleston.chiang@med.usc.edu.
Source: Genes & nutrition [Genes Nutr] 2026 Jun 18. Date of Electronic Publication: 2026 Jun 18.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: Germany NLM ID: 101280108 Publication Model: Print-Electronic Cited Medium: Print ISSN: 1555-8932 (Print) Linking ISSN: 15558932 NLM ISO Abbreviation: Genes Nutr
Database: MEDLINE Ultimate
Description
ISSN:1555-8932
DOI:10.1186/s12263-026-00811-1